Update app.py

app.py

@@ -1,121 +1,3 @@
-# import streamlit as st
-# import hashlib
-# import os
-# import aiohttp
-# import asyncio
-# import time
-# from langsmith import traceable
-# import random
-# import discord
-# from transformers import pipeline
-# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-# import numpy as np
-# from sklearn.metrics.pairwise import cosine_similarity
-# from pydantic import BaseModel
-# from typing import List, Optional
-# from tqdm import tqdm
-# import re
-# import os
-# from teapotai import TeapotAI, TeapotAISettings
-# import pandas as pd
-
-
-# st.set_page_config(page_title="TeapotAI Discord Bot", page_icon=":robot_face:", layout="wide")
-
-
-
-# wiki_data = pd.read_csv("https://docs.google.com/spreadsheets/d/1NNbdQWIfVHq09lMhVSN36_SkGu6XgmKTXgBWPyQcBpk/export?format=csv")
-# documents = wiki_data['content'].str.split('\n\n').explode().reset_index(drop=True)
-# documents
-
-# # Intialize Teapot with documents
-# teapot_ai = TeapotAI(documents=documents.to_list(), settings=TeapotAISettings(rag_num_results=7))
-
-# # I apologize, but I'm not qualified to provide personalized advice or recommendations.
-# # Latent caching is a feature of the training process that saves intermediate data and can be used to speed up the training.
-# # Yes
-# # I'm sorry, but I don't have information on the optimizers.
-# # 2
-# # The Concepts tab is made up of the following elements: For expert users: Embedding Training To get a general overview of the UI, please read the Quick Start Guide first.
-
-
-# def log_time(func):
-#     async def wrapper(*args, **kwargs):
-#         start_time = time.time()
-#         result = await func(*args, **kwargs)  # Make it awaitable
-#         end_time = time.time()
-#         print(f"{func.__name__} executed in {end_time - start_time:.4f} seconds")
-#         return result
-#     return wrapper
-
-
-# # @traceable
-# @log_time
-# async def handle_chat(user_input):
-#     def run_sync_query():
-#         return teapot_ai.query(user_input)
-
-#     output_text = await asyncio.to_thread(run_sync_query)
-
-#     return output_text
-
-
-# st.write("418 I'm a teapot")
-
-# DISCORD_TOKEN = os.environ.get("discord_key")
-
-# # Create an instance of Intents and enable the required ones
-# intents = discord.Intents.default()  # Default intents enable basic functionality
-# intents.messages = True  # Enable message-related events
-
-# # Create an instance of a client with the intents
-# client = discord.Client(intents=intents)
-
-# # Event when the bot has connected to the server
-# @client.event
-# async def on_ready():
-#     print(f'Logged in as {client.user}')
-
-# # Event when a message is received
-# @client.event
-# async def on_message(message):
-#     # Check if the message is from the bot itself to prevent a loop
-#     if message.author == client.user:
-#         return
-    
-#     # Exit the function if the bot is not mentioned
-#     if f'<@{client.user.id}>' not in message.content:
-#         return 
-        
-#     print(message.content)
-
-#     is_debug = "debug:" in message.content or "Debug:" in message.content
-#     async with message.channel.typing():
-#         cleaned_message=message.content.replace("debug:", "").replace("Debug:","").replace(f'<@{client.user.id}>',"")
-#         response = await handle_chat(cleaned_message)
-#         print(response)
-#         sent_message = await message.reply(response)
-    
-#         # Create a thread from the sent message
-#         if is_debug:
-#             thread = await sent_message.create_thread(name=f"""Debug Thread: '{cleaned_message[:80]}'""", auto_archive_duration=60)
-        
-#             # Send a message in the created thread
-#             await thread.send(debug_info)
-
-
-# @st.cache_resource
-# def initialize():
-#     st.session_state["initialized"] = True
-#     client.run(DISCORD_TOKEN)
-
-#     return 
-
-# initialize()
-
-
-
-
 import streamlit as st
 import os
 import aiohttp
@@ -144,7 +26,8 @@ client = discord.Client(intents=intents)
 async def handle_teapot_inference(server_name, user_input):
     teapot_instance = CONFIG.get(server_name, CONFIG["Teapot AI"])
     print(f"Using Teapot instance for server: {server_name}")
-    response = await teapot_instance.query(user_input)
+    # Running query in a separate thread to avoid blocking the event loop
+    response = await asyncio.to_thread(teapot_instance.query, user_input)
     return response
 
 
@@ -162,7 +45,7 @@ async def on_message(message):
         return
 
     server_name = message.guild.name if message.guild else "Teapot AI"
-    server_name ="OneTrainer"
+    server_name = "OneTrainer"  # This seems to be hardcoded, but you can change it based on your logic
     async with message.channel.typing():
         cleaned_message = message.content.replace(f'<@{client.user.id}>', "").strip()
         response = await handle_teapot_inference(server_name, cleaned_message)